Cloud Masking for Remotely Sensed Data Using Spectral and Principal Components Analysis
Two methods of cloud masking tuned to tropical conditions have been developed, based on spectral analysis and Principal Components Analysis (PCA) of Moderate Resolution Imaging Spectroradiometer (MODIS) data. In the spectral approach, thresholds were applied to four reflective bands (1, 2, 3, and 4), three thermal bands (29, 31 and 32), the band 2/band 1 ratio, and the difference between band 29 and 31 in order to detect clouds. The PCA approach applied a threshold to the first principal component derived from the seven quantities used for spectral analysis. Cloud detections were compared with the standard MODIS cloud mask, and their accuracy was assessed using reference images and geographical information on the study area.
Keywords:cloud masking, spectral analysis, principal components analysis, reflectance, brightness temperature
W. B. Rossow, Gardner, “Cloud detection using satellite measurement of infrared and visible radiances for ISCCP”. Journal of Climate, Vol. 6, pp. 2341 – 2369, 1993 DOI: https://doi.org/10.1175/1520-0442(1993)006<2341:CDUSMO>2.0.CO;2
S. A. Ackerman, K. I. Strabala, W. P. Menzel, R. A., Frey, C. C. Moeller, L. E. Gumley, B. A. Baum, C. Schaaf, G. Riggs, Discriminating Clear-Sky from Cloud with MODIS - Algorithm Theoretical Basis Document. Products: MOD35. ATBD Reference Number: ATBD-MOD-06, Greenbelt: MODIS Cloud Mask Team, 2002
R. W. Saunders, “An automated scheme for the removal of cloud contamination form AVHRR radiances over Western Europe”, International Journal of Remote Sensing, Vol. 7, pp. 867–886, 1986 DOI: https://doi.org/10.1080/01431168608948896
A. M. Logar, D. E. Lloyd, E. M. Corwin, M. L. Penaloza, R. E. Feind, T. A. Berendes, K. Kuo, R. M. Welch, “The ASTER polar cloud mask”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, No. 4, pp. 1302–1312, 1998 DOI: https://doi.org/10.1109/36.701080
G. B. Franya, A. P. Cracknell, “A simple cloud masking approach using NOAA AVHRR daytime data for tropical areas”, International Journal of Remote Sensing, Vol. 16, No. 9, pp.1697–1705, 1995 DOI: https://doi.org/10.1080/01431169508954506
J. Bendix, R. Rollenbeck, W. E. Palacios, “Cloud detection in the Tropics – a suitable tool for climate – ecological studies in the high mountains of Equador”, International Journal of Remote Sensing, Vol. 25, No. 21, pp. 4521 – 4540, 2004 DOI: https://doi.org/10.1080/01431160410001709967
P. H. Swain, S. M. Davis, 1978. Remote Sensing: The Quantitative Approach. New York: McGraw-Hill
R. W. Saunders, K. T. Kriebel, “An improved method for detecting clear sky and cloudy radiances from AVHRR data”, International Journal of Remote Sensing, Vol. 9, No. 1, pp.123–150, 1988 DOI: https://doi.org/10.1080/01431168808954841
W. P. Loughlin, “Principal component analysis for alteration mapping”, Photogrammetry Engineering and Remote Sensing, Vol. 57, No. 9, pp. 1163-1169, 1991
D. W. Hillger, J. D. Clark, “Principal component image analysis of MODIS for volcanic ash. Part 1: Most important bands and implications for future GOES imagers”, Journal of Applied Meteorology, Vol. 41, No. 10, pp. 985-1001, 2002 DOI: https://doi.org/10.1175/1520-0450(2002)041<0985:PCIAOM>2.0.CO;2
A. T. A Jose, G. R. Francisco, P. L. Mercedes, M. Canton, “An automatic cloud-masking system using backpro neural nets for AVHRR scenes”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, No. 4, pp. 826-831, 2003 DOI: https://doi.org/10.1109/TGRS.2003.809930
S. R. Yhann, J. J. Simpson, “Application of neural networks to AVHRR cloud segmentation”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 33, No. 3, pp. 590-604, 1995 DOI: https://doi.org/10.1109/36.387575
C. O. Justice, E. Vermote, J. R. G. Townshend, R. Defries, D. P. Roy, D. K. Hall, V. V. Salomonson, J. L. Privette, G. Riggs, A. Strahler, W. Lucht, R. B. Myneni, Y. Knyazikhin, S. W. Running, R. R Nemani, W. Zhengming, A. R. Huete, W. Van Leeuwen, R. E. Wolfe, L. Giglio, Muller, P. Lewis, M. J. Barnsley, “The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, No. 4, pp.1228-1249, 1998 DOI: https://doi.org/10.1109/36.701075
F. Sedano, P. Kempeneers, P. Strobl, J. Kucera, P. Vogt, L. Seebach, J. San-Miguel-Ayanz, “A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors”, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 66, pp. 588-596, 2011 DOI: https://doi.org/10.1016/j.isprsjprs.2011.03.005
R. G. Congalton, “A review of assessing the accuracy of classifications of remotely sensed data”, Remote Sensing of Environment, Vol. 37, No. 1, pp. 35-46, 1991 DOI: https://doi.org/10.1016/0034-4257(91)90048-B
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